“We see this as the future of music,” said Eddie Wenrick, chief executive of Hitlab.com,a Montreal startup that aims to be the big new platform for farming musical talent. The company is a blend of MySpace– the social networking site popular among bands –and Canadian Idol. Members create profiles and add their songs for all to hear and buy. But for $30, they can get Hitlab’s software, called Dynamic Hit Scoring, to analyze their music’s hit potential. If they score highly, they increase their chance of signing a record contract.

Every three months, the four Hitlab users with the highest DHS score are invited to a talent show before a panel of industry honchos. The winners get coupled with managers and hopefully ink album contracts.

Hitlab would get a cut of the deal and publishing rights, and fame-seeking virtuosos get the exposure, Wenrick said.

“It’ll be a springboard to kick-start their careers,” he said. “We like to say we’re a baseball farm team before they go to the major leagues.”

Wenrick, a veteran of the music industry — he was an executive at Columbia Records and Epic Records and ran several talent management firms — understands that letting a robot pick new talent is exceptionally inhuman in a human-driven enterprise. This is why he also invites another top four members, as voted by other users, to the showcase.

“This is for users who don’t have a hit song, but have a large following and show potential,” he said.

And from the website on how DHS works:

To analyze music, the system breaks down the sound frequencies of a song into 78 variables such as tone, pitch, tempo, etc. If a song has very similar patterns to a song that was at the top of the billboard for a long period of time, the DHS score will be high. On the other hand, if the song has a moderately similar pattern to a song that was low on the billboard charts for a short period of time, the DHS score will be lower. By comparing a song to the database that holds the recent trends in music, we can evaluate how appealing the mathematical patterns of the sound frequencies are to the human ear, thereby evaluating a song’s hit potential.Step by step:

Each MP3 song is digitized and parceled into tens of hundreds of short audio files.

A set of unique features (78 isolated variables) of the audio contents is extracted from each segment.

A full set of identifying features is created for each piece of MP3 content.

The complete set is then stored in the database.

Each MP3 is ranked according to its peak position in the Billboard compilation using the algorithms and stored in the database for future analysis.

I don’t know if something like this actually works. I guess it would for “pop” songs that may have many similar characteristics. My concern is whether a Bob Dylan or Bruce Springsteen, who didn’t sound like the prevailing pop at the time, would make it threw this type of screening…